Mesoscale convective systems (MCSs) occasionally develop over the East China Sea (ECS) in the Baiu frontal zone under both the atmospheric and oceanic influence. The factors that determine their predictability have not been fully understood yet. This study investigates the uncertainties affecting two MCSs observed by research vessels on 19 June 2022 using regional ensemble simulations. These MCSs have contrasting features: the first was triggered by an atmospheric mesoscale disturbance, while the second was induced by the boundary layer destabilization over the warm Kuroshio current.

The first MCS shows high variability in the synoptic-scale uncertainties detected by the breeding ensemble. The best-performing member successfully represents the strong meso-β-scale cyclone and the frontal structure with deep moist layers. The ensemble simulations are less skillful for the second MCS than the first. The enhanced surface turbulent heat flux in the sea surface temperature (SST) frontal zone is found to be significantly correlated to the precipitation due to the second MCS despite the cold bias of SST that is commonly imposed on all members. The dense upper-air information from the vessels significantly improves the representation of the sharp frontal structure associated with the first MCS, but has little impact on the second MCS probably due to the underestimation of the boundary layer moistening. This case study indicates that the predictability of MCSs over the ECS depends on their development mechanisms, and that the incorporation of uncertainties in both the atmosphere and ocean are important for the ensemble forecasting of these MCSs.

In mid-December 2023, East Asia experienced an extreme sea-effect snowstorm, with snowfall intensity and snow depth breaking historical records. Based on FengYun (FY) meteorological satellite datasets, the atmospheric circulation, the evolution of the sea-effect clouds, and the marine and atmospheric environments are examined. The results show that the temperature anomalies at 850 hPa from the polar regions to East Asia and the Northwest Pacific exhibited a “positive-negative-positive” pattern in early December, which is in favor of the polar vortex moving away from the polar region to lower latitudes causing cold waves. Caused by the northerly winds over the ocean the sea-effect snowstorm cloud systems exhibit as a wide range of cellular cumulus moving towards the land. The weakening wind speed is beneficial for the maintaining of the sea-effect snowstorm. The average cloud top temperature (CTT) of sea-effect snowstorm clouds over the Shandong Peninsula is from −18 °C to −10 °C, and the cloud top height (CTH) is about 1.5 km, showing significant differences from that of the cold front snowstorm clouds. The precipitation rate from FY-3G precipitation measurement radar (PMR) shows that the precipitation top of the cellular cumulus in the Yellow Sea and the East China Sea is 2.0 – 2.5 km, and the maximum precipitation rate is 0.5 – 1.0 mm h⁻¹. The high sea surface temperature (SST) provides warm and humid conditions for the cellular cumulus. The colder air moving into warmer and more humid sea surface can result in higher development of cellular cumulus and increasing precipitation rate. The overall performance is characterized by the higher SST, higher atmospheric humidity layers, higher temperature inversion layers, lower CTT, higher CTH, and greater precipitation intensity on the western coast of Honshu Island in Japan compared to the Shandong Peninsula. Additionally, the topography has impact on the distribution and intensity of sea-effect snowstorm.

Simultaneous observations using a long-duration balloon and the PANSY radar, a large-scale atmospheric radar, were performed at Syowa Station in the Antarctic, from January to February 2022. They captured near-inertial frequency gravity waves (NIGWs) in the lower stratosphere. The analysis using both datasets and the latest reanalysis ERA5 revealed that two NIGW packets with an upward group velocity and short vertical wavelengths of less than 3 km propagated northeastward and eastward above Syowa Station. Although the NIGWs over Syowa Station were qualitatively represented by ERA5, their amplitudes were underestimated. In addition, the latter NIGW packet was observed by the long-duration balloon, but not represented by ERA5. It could be because the vertical wavelength of NIGW became shorter than the lower limit of vertical wavelength explicitly represented in ERA5 by entering the high static stability region around the balloon, or due to explicit and implicit diffusion and/or misrepresentation of the position of the NIGW packet in the model. This result implies the difficulty to explicitly represent the behavior of NIGWs with short vertical wavelengths even in the high-resolution simulation.

The study investigates the relationship between climate pattern, rainfall, and internal warm cloud structure in Thailand using ground-based meteorological and satellite data. Situated in the tropical climate zone, Thailand faces drought conditions exacerbated by changes in warm cloud patterns due to climate change. Results indicate a negative correlation between rainfall and Oceanic Niño Index (ONI) and Pacific Decadal Oscillation (PDO), with rainfall decreasing as ONI and PDO values increase, especially in April and October. In contrast, Indian Ocean Dipole (IOD) shows a weaker correlation with the rainfall during the period from 1991 to 2022.

During the period from 2006 to 2014, the internal warm cloud structure over Thailand was analyzed using contoured frequency by optical depth diagrams (CFODDs) derived from CloudSat Cloud Profiling Radar (CPR) and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). The results show the warm cloud process, indicated by the transfer of cloud droplets to drizzle and rain as cloud particle size increases near the cloud top. The cloud droplet mode occurs from 4 µm to 15 µm, drizzle mode occurs from 15 µm to 21 µm and dominance of rain mode occurs above 21 µm.

Differences in cloud structures are observed under seasonal and El Niño–Southern Oscillation (ENSO) phases, with the warm clouds contain larger cloud droplet effective radius (R_e) during the wet season compared to the dry season. Meanwhile, in cloud structure exhibit thicker cloud and faster transfer drizzle mode to rain mode with R_e increasing during La Niña phase compared to El Niño phase. These differences in cloud structures are attributed to variations in aerosols, differences in humidity, and temperature influenced by geographical characteristics.

We are conducting a 5-km long-term atmospheric regional reanalysis for Japan with assimilating conventional observations (RRJ-Conv). RRJ-Conv is produced with a one-way double-nesting system consisting of a nonhydrostatic regional model and a local ensemble transform Kalman filter (LETKF), which is driven by the Japanese 55-year reanalysis (JRA-55). The assimilated data are limited to long-term available data, specifically surface in-situ pressure observations, upper-air radiosonde observations, and tropical cyclone center positions.

This paper overviews the performance of RRJ-Conv for 20 years from July 2001 to June 2021, mainly focusing on precipitation and exploring added values to JRA-55. RRJ-Conv is confirmed to maintain long-term consistency of analysis quality. Compared to JRA-55, RRJ-Conv reduces biases in central pressures of tropical cyclones, maintaining position reproducibility. RRJ-Conv represents detailed spatial distributions of monthly precipitation, extreme values for daily precipitation, and their interannual variation more realistically than JRA-55. The improvements to JRA-55 are demonstrated for some extreme events, involving a tropical cyclone, Baiu front and East Asian winter monsoon.